Table of Contents

Enum CamshiftMode

Namespace
VisioForge.Core.Types.VideoProcessing
Assembly
VisioForge.Core.dll

Specifies the color space mode to be used by the Camshift (Continuously Adaptive Mean-Shift) tracking algorithm. The choice of color space can significantly impact the robustness and accuracy of object tracking.

public enum CamshiftMode

Fields

RGB = 0

The tracker will process raw high-intensity RGB (Red, Green, Blue) values. This mode is sensitive to lighting changes but can be effective for objects with distinct color signatures.

HSL = 1

The tracker will perform an RGB-to-HSL (Hue, Saturation, Lightness) conversion and primarily use the Hue component. This mode is generally more robust to changes in lighting conditions.

Mixed = 2

The tracker will use a combination of HSL with some lightness information. This mode attempts to balance color robustness with some intensity information.

Remarks

Camshift is an algorithm for tracking non-rigid objects. It relies on a color histogram of the target object. Different color spaces offer varying degrees of robustness to changes in lighting and object orientation. RGB mode processes raw color intensity values, sensitive to lighting but good for distinct color signatures. HSL mode converts to Hue-Saturation-Lightness and primarily uses Hue, providing robustness to lighting variations. Mixed mode combines HSL with lightness information, balancing color robustness with intensity data. Camshift extends the Mean-Shift algorithm by adapting the search window size and orientation to match object changes. The algorithm is particularly effective for tracking faces, hands, or other colored objects in real-time video. Color space choice affects tracking performance: HSL is generally preferred for variable lighting, RGB for controlled environments. Applications include object tracking in surveillance, human-computer interaction, augmented reality, and robotics. Camshift requires an initial target region and builds a color histogram for subsequent frame tracking. Performance depends on color distinctiveness, lighting conditions, occlusion, and object motion speed.